Start Date

10-12-2017 12:00 AM

Description

Data visualizations in the form of graphs are one of the most important ways to communicate information. Graphs displaying 3-dimensions (3-D) of data have garnered research interest, but there is no consensus about the best 3-D graph. In this work, we ask the question, “What is the best kind of graphs for displaying three continuous variables?” “Best” is defined in three ways: accuracy, speed, and neural activation measured by functional magnetic resonance imaging (fMRI). Based on the theory of evolution, we hypothesize that people will be more accurate and faster in reading graphs that mimic visual stimuli in the natural environment, as does the 3-D surface graph. We find that participants are more accurate at reading 3-D surface graphs than any other of five types of graph we studied and that participants show greater activation in the ventral stream of the visual system when reading 3-D surface graphs.

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Dec 10th, 12:00 AM

Discovery of the Optimal Visualization for Representing Three Dimensions of Data Using Functional Magnetic Resonance Imaging

Data visualizations in the form of graphs are one of the most important ways to communicate information. Graphs displaying 3-dimensions (3-D) of data have garnered research interest, but there is no consensus about the best 3-D graph. In this work, we ask the question, “What is the best kind of graphs for displaying three continuous variables?” “Best” is defined in three ways: accuracy, speed, and neural activation measured by functional magnetic resonance imaging (fMRI). Based on the theory of evolution, we hypothesize that people will be more accurate and faster in reading graphs that mimic visual stimuli in the natural environment, as does the 3-D surface graph. We find that participants are more accurate at reading 3-D surface graphs than any other of five types of graph we studied and that participants show greater activation in the ventral stream of the visual system when reading 3-D surface graphs.